Creating PNGs of the Direct Graphs

Florida Polytechnic University COP5090.01

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Introduction

On this page we have some code as well as images which is used to create high-quality PNGs of the directed graphs for every project within the jsons directory. We have taken the code from the example using 3choices on the previous page and made it ambiguous and modular in the script sumo_dg_viewer.R. We start by including the source file sumo_dg_viewer.R. An additional note, we decide that the statnet graphs are visually cleaner than the igraph graphs and so all of the PNGs produced are statnet graphs.

source(file="../scripts/sumo_dg_viewer.R")

3choices

# 3choices
png(file="../exports/directed_graphs/3choices.dg.png",width=1000,height=500,units="px",res=NA)
adjacency.matrix.3choices <- json2am('3choices') 

[1] "Filling adjaency matrix"
============================================================================================================================

adjacency.network.3choices <- network(
  adjacency.matrix.3choices,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.3choices,
  gmode="digraph",
  label=adjacency.network.3choices%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=1.5,
  arrowhead.cex=1.5
)

3choices.dg.png

Davenport

# Davenport
png(file="../exports/directed_graphs/Davenport.dg.png",width=10000,height=7000,units="px",res=NA)
if (!exists("adjacency.matrix.Davenport")){
  adjacency.matrix.Davenport <- json2am('Davenport')
}
  
adjacency.network.Davenport <- network(
  adjacency.matrix.Davenport,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.Davenport,
  gmode="digraph",
  label=adjacency.network.Davenport%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=0.3,
  arrowhead.cex=0.3
)

Davenport.dg.png

flpoly

# flpoly
png(file="../exports/directed_graphs/flpoly.dg.png",width=3000,height=3600,units="px",res=NA)
adjacency.matrix.flpoly <- json2am('flpoly')

[1] "Filling adjaency matrix"
============================================================================================================================

adjacency.network.flpoly <- network(
  adjacency.matrix.flpoly,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.flpoly,
  gmode="digraph",
  label=adjacency.network.flpoly%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=0.3,
  arrowhead.cex=0.3
)

flpoly.dg.png

grid2

# grid2
png(file="../exports/directed_graphs/grid2.dg.png",width=1000,height=700,units="px",res=NA)
adjacency.matrix.grid2 <- json2am('grid2')

[1] "Filling adjaency matrix"
============================================================================================================================

adjacency.network.grid2 <- network(
  adjacency.matrix.grid2,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.grid2,
  gmode="digraph",
  label=adjacency.network.grid2%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=1,
  arrowhead.cex=1
)

grid2

Haines_City

# Haines_City
png(file="../exports/directed_graphs/Haines_City.dg.png",width=10000,height=7000,units="px",res=NA)
if (!exists("adjacency.matrix.Haines_City")){
  adjacency.matrix.Haines_City <- json2am('Haines_City')
}
  
adjacency.network.Haines_City <- network(
  adjacency.matrix.Haines_City,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.Haines_City,
  gmode="digraph",
  label=adjacency.network.Haines_City%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=0.3,
  arrowhead.cex=0.3
)

Haines_City

intersection_1

# intersection_1
png(file="../exports/directed_graphs/intersection_1.dg.png",width=1000,height=700,units="px",res=NA)
adjacency.matrix.intersection_1 <- json2am('intersection_1')

[1] "Filling adjaency matrix"
============================================================================================================================

adjacency.network.intersection_1 <- network(
  adjacency.matrix.intersection_1,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.intersection_1,
  gmode="digraph",
  label=adjacency.network.intersection_1%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=1,
  arrowhead.cex=1
)

intersection_1.dg.png

leopard

# leopard
png(file="../exports/directed_graphs/leopard.dg.png",width=3000,height=3600,units="px",res=NA)
adjacency.matrix.leopard <- json2am('leopard')

[1] "Filling adjaency matrix"
============================================================================================================================

adjacency.network.leopard <- network(
  adjacency.matrix.leopard,
  matrix.type="adjacency",
  directed=FALSE,
  cignore.eval=FALSE,
  names.eval="value"
)
gplot(
  adjacency.network.leopard,
  gmode="digraph",
  label=adjacency.network.leopard%v%'vertex.names',
  boxed.labels=TRUE,
  vertex.cex=0.3,
  arrowhead.cex=0.3
)

leopard.dg.png